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Category: robotics/AI – Page 1844

Researchers from Russian corporation Neurobotics and the Moscow Institute of Physics and Technology have found a way to visualize a person’s brain activity as actual images mimicking what they observe in real time. This will enable new post-stroke rehabilitation devices controlled by brain signals. The team published its research as a preprint on bioRxiv and posted a video online showing their “mind-reading” system at work.

To develop devices controlled by the brain and methods for cognitive disorder treatment and post-stroke rehabilitation, neurobiologists need to understand how the brain encodes information. A key aspect of this is studying the brain activity of people perceiving visual information, for example, while watching a video.

The existing solutions for extracting observed images from brain signals either use functional MRI or analyze the signals picked up via implants directly from neurons. Both methods have fairly limited applications in clinical practice and everyday life.

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A new way to calculate the interaction between a metal and its alloying material could speed the hunt for a new material that combines the hardness of ceramic with the resilience of metal.

The discovery, made by engineers at the University of Michigan, identifies two aspects of this interaction that can accurately predict how a particular alloy will behave—and with fewer demanding, from-scratch quantum mechanical calculations.

“Our findings may enable the use of machine learning algorithms for alloy design, potentially accelerating the search for better alloys that could be used in turbine engines and nuclear reactors,” said Liang Qi, assistant professor of materials science and engineering who led the research.

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While it seems we are making great strides in unlocking the mysteries of the Universe, there is a sizable hole in what we know – up to 95% of the cosmos appears to be missing. We are talking about dark matter and dark energy, two useful, groundbreaking, but yet-to-be-directly-observed explanations for the vast majority of what exists. While there have been various attempts to pin down these ideas, inferred from their gravitational effects, a recent theory from a University of Oxford scientist claims to do away with them entirely. Instead, his model proposes something which may be even more unusual – what if the Universe is actually filled with a “dark fluid” possessing “negative mass”?

Dark matter takes up 27% of the known Universe (per NASA), while dark energy, a repulsive force that makes the Universe expand, gets 68%. Only 5% of the Universe is the observable world, including us and our planet. According to the model, proposed by Dr. Jamie Farnes, both dark matter and dark energy are unified in a fluid which has “negative gravity”. It repels all other material away.

“Although this matter is peculiar to us, it suggests that our cosmos is symmetrical in both positive and negative qualities,” wrote Farnes, astrophysicist, cosmologist and data scientist who worked at Oxford at the time of publishing his paper, and has since moved on to Faculty, a leading AI company.

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The three-body problem, one of the most notoriously complex calculations in physics, may have met its match in artificial intelligence: a new neural network promises to find solutions up to 100 million times faster than existing techniques.

First formulated by Sir Isaac Newton, the three-body problem involves calculating the movement of three gravitationally interacting bodies – such as the Earth, the Moon, and the Sun, for example – given their initial positions and velocities.

It might sound simple at first, but the ensuing chaotic movement has stumped mathematicians and physicists for hundreds of years, to the extent that all but the most dedicated humans have tried to avoid thinking about it as much as possible.

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